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cs.LG2026
OrderDP: A Theoretically Guaranteed Lossless Dynamic Data Pruning Framework
Chenhan Jin, Shengze Xu, Qingsong Wang +3
Data pruning (DP), as an oft-stated strategy to alleviate heavy training burdens, reduces the volume of training samples according to a well-defined pruning method while striving f…
cs.LG2024
Efficient Private SCO for Heavy-Tailed Data via Averaged Clipping
Chenhan Jin, Kaiwen Zhou, Bo Han +2
We consider stochastic convex optimization for heavy-tailed data with the guarantee of being differentially private (DP). Most prior works on differentially private stochastic conv…